{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Online Retails Purchase"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Introduction:\n",
    "\n",
    "\n",
    "\n",
    "### Step 1. Import the necessary libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# set the graphs to show in the jupyter notebook\n",
    "%matplotlib inline\n",
    "\n",
    "# set seabor graphs to a better style\n",
    "sns.set(style=\"ticks\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 2. Import the dataset from this [address](https://raw.githubusercontent.com/guipsamora/pandas_exercises/master/Visualization/Online_Retail/Online_Retail.csv). "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 3. Assign it to a variable called online_rt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>InvoiceNo</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>UnitPrice</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536365</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>12/1/10 8:26</td>\n",
       "      <td>2.55</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>536365</td>\n",
       "      <td>71053</td>\n",
       "      <td>WHITE METAL LANTERN</td>\n",
       "      <td>6</td>\n",
       "      <td>12/1/10 8:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>536365</td>\n",
       "      <td>84406B</td>\n",
       "      <td>CREAM CUPID HEARTS COAT HANGER</td>\n",
       "      <td>8</td>\n",
       "      <td>12/1/10 8:26</td>\n",
       "      <td>2.75</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029G</td>\n",
       "      <td>KNITTED UNION FLAG HOT WATER BOTTLE</td>\n",
       "      <td>6</td>\n",
       "      <td>12/1/10 8:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029E</td>\n",
       "      <td>RED WOOLLY HOTTIE WHITE HEART.</td>\n",
       "      <td>6</td>\n",
       "      <td>12/1/10 8:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  InvoiceNo StockCode                          Description  Quantity  \\\n",
       "0    536365    85123A   WHITE HANGING HEART T-LIGHT HOLDER         6   \n",
       "1    536365     71053                  WHITE METAL LANTERN         6   \n",
       "2    536365    84406B       CREAM CUPID HEARTS COAT HANGER         8   \n",
       "3    536365    84029G  KNITTED UNION FLAG HOT WATER BOTTLE         6   \n",
       "4    536365    84029E       RED WOOLLY HOTTIE WHITE HEART.         6   \n",
       "\n",
       "    InvoiceDate  UnitPrice  CustomerID         Country  \n",
       "0  12/1/10 8:26       2.55     17850.0  United Kingdom  \n",
       "1  12/1/10 8:26       3.39     17850.0  United Kingdom  \n",
       "2  12/1/10 8:26       2.75     17850.0  United Kingdom  \n",
       "3  12/1/10 8:26       3.39     17850.0  United Kingdom  \n",
       "4  12/1/10 8:26       3.39     17850.0  United Kingdom  "
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url = 'https://raw.githubusercontent.com/guipsamora/pandas_exercises/master/Visualization/Online_Retail/Online_Retail.csv'\n",
    "online_rt = pd.read_csv(url)\n",
    "\n",
    "online_rt.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 4. Create a histogram with the 10 countries that have the most 'Quantity' ordered except UK"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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70fseV2YkIiIiUSwKREREJIpFgYiIiESxKBAREZEoFgUiIiISxaJAREREolgUiIiISBSL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\nT0+cPHkSr7/+OsLDw7F27Vq9PT+Lgh7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      "text/plain": [
       "<matplotlib.figure.Figure at 0x122453dd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# group by the Country\n",
    "countries = online_rt.groupby('Country').sum()\n",
    "\n",
    "# sort the value and get the first 10 after UK\n",
    "countries = countries.sort_values(by = 'Quantity',ascending = False)[1:11]\n",
    "\n",
    "# create the plot\n",
    "countries['Quantity'].plot(kind='bar')\n",
    "\n",
    "# Set the title and labels\n",
    "plt.xlabel('Countries')\n",
    "plt.ylabel('Quantity')\n",
    "plt.title('10 Countries with more orders')\n",
    "\n",
    "# show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 5.  Exclude negative Quatity entries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>InvoiceNo</th>\n",
       "      <th>StockCode</th>\n",
       "      <th>Description</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>InvoiceDate</th>\n",
       "      <th>UnitPrice</th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>536365</td>\n",
       "      <td>85123A</td>\n",
       "      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n",
       "      <td>6</td>\n",
       "      <td>12/1/10 8:26</td>\n",
       "      <td>2.55</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>536365</td>\n",
       "      <td>71053</td>\n",
       "      <td>WHITE METAL LANTERN</td>\n",
       "      <td>6</td>\n",
       "      <td>12/1/10 8:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>536365</td>\n",
       "      <td>84406B</td>\n",
       "      <td>CREAM CUPID HEARTS COAT HANGER</td>\n",
       "      <td>8</td>\n",
       "      <td>12/1/10 8:26</td>\n",
       "      <td>2.75</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029G</td>\n",
       "      <td>KNITTED UNION FLAG HOT WATER BOTTLE</td>\n",
       "      <td>6</td>\n",
       "      <td>12/1/10 8:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>536365</td>\n",
       "      <td>84029E</td>\n",
       "      <td>RED WOOLLY HOTTIE WHITE HEART.</td>\n",
       "      <td>6</td>\n",
       "      <td>12/1/10 8:26</td>\n",
       "      <td>3.39</td>\n",
       "      <td>17850.0</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  InvoiceNo StockCode                          Description  Quantity  \\\n",
       "0    536365    85123A   WHITE HANGING HEART T-LIGHT HOLDER         6   \n",
       "1    536365     71053                  WHITE METAL LANTERN         6   \n",
       "2    536365    84406B       CREAM CUPID HEARTS COAT HANGER         8   \n",
       "3    536365    84029G  KNITTED UNION FLAG HOT WATER BOTTLE         6   \n",
       "4    536365    84029E       RED WOOLLY HOTTIE WHITE HEART.         6   \n",
       "\n",
       "    InvoiceDate  UnitPrice  CustomerID         Country  \n",
       "0  12/1/10 8:26       2.55     17850.0  United Kingdom  \n",
       "1  12/1/10 8:26       3.39     17850.0  United Kingdom  \n",
       "2  12/1/10 8:26       2.75     17850.0  United Kingdom  \n",
       "3  12/1/10 8:26       3.39     17850.0  United Kingdom  \n",
       "4  12/1/10 8:26       3.39     17850.0  United Kingdom  "
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "online_rt = online_rt[online_rt.Quantity > 0]\n",
    "online_rt.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 6. Create a scatterplot with the Quantity per UnitPrice by CustomerID for the top 3 Countries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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FhYXk5uZy9OhRwsLCCA8PJz09HYD09HQiIyOx2+3YbDaysrIwxrB161YiIiKu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\nS5MmTbDb7fj5+REREcGePXu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      "text/plain": [
       "<matplotlib.figure.Figure at 0x128b11e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# groupby CustomerID\n",
    "customers = online_rt.groupby(['CustomerID','Country']).sum()\n",
    "\n",
    "# there is an outlier with negative price\n",
    "customers = customers[customers.UnitPrice > 0]\n",
    "\n",
    "# get the value of the index and put in the column Country\n",
    "customers['Country'] = customers.index.get_level_values(1)\n",
    "\n",
    "# top three countries\n",
    "top_countries =  ['Netherlands', 'EIRE', 'Germany']\n",
    "\n",
    "# filter the dataframe to just select ones in the top_countries\n",
    "customers = customers[customers['Country'].isin(top_countries)]\n",
    "\n",
    "################\n",
    "# Grap Section #\n",
    "################\n",
    "\n",
    "# creates the FaceGrid\n",
    "g = sns.FacetGrid(customers, col=\"Country\")\n",
    "\n",
    "# map over a make a scatterplot\n",
    "g.map(plt.scatter, \"Quantity\", \"UnitPrice\", alpha=1)\n",
    "\n",
    "# adds legend\n",
    "g.add_legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### BONUS: Create your own question and answer it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
